Practical guides on LLM cost optimization, model routing, and AI infrastructure.
AWS Bedrock gives you a managed AI platform inside AWS. PromptUnit cuts your LLM costs automatically with one line of code. Different tools, different jobs.
Helicone is an LLM observability proxy. PromptUnit is an LLM cost optimization layer. They answer different questions. Here is which one you actually need.
Langfuse is an open-source LLM observability and tracing platform. PromptUnit is a cost optimization proxy. They do different things and often belong together.
LangSmith is LangChain's evaluation and debugging platform for LLM applications. PromptUnit is a cost optimization proxy. They solve different problems and are often used together.
Portkey and PromptUnit are both LLM gateways with routing and fallback. But Portkey optimizes for control and reliability. PromptUnit optimizes for cost reduction. Here is the difference.
OpenAI at $0.02/M, Voyage 4 at $0.06/M, Cohere Embed v4 at $0.12/M. How to route embedding calls by workload type to match cost to quality requirements.
GLM-5.1 scored 58.4 on SWE-Bench Pro, beating GPT-5.4 and Claude Opus 4.6, at $0.95 per million input tokens. The coding routing default just changed.
Current SWE-bench scores, HumanEval rankings, and cost-quality matrix for the best coding LLMs in 2026. Which model to use and at what price.
A routing-first guide to the best LLM for coding in 2026. Which coding tasks go to which model, cost per task type, and SWE-bench benchmark scores.
Claude Haiku 4.5 costs $1/$5 per million tokens. Sonnet 4.6 costs $3/$15. Here is when Haiku matches Sonnet and when it fails, with routing logic for each task type.
GPT-4o-mini costs $0.15/$0.60 per million tokens vs GPT-4o at $2.50/$10. Full pricing breakdown, cost comparison at scale, and which tasks justify the switch.
What metrics to track for LLM cost visibility, how to set up monitoring, how to catch cost spikes, and how to enforce budgets in production.
OpenRouter is a model marketplace. LiteLLM is an open-source proxy. PromptUnit is a cost optimization layer. Different jobs. Here is which to use for what.
An AI router directs LLM API calls to the optimal model by cost, quality, and task type. How it works, rule-based vs ML routing, and when you need one.
An LLM gateway is a control layer between your app and model providers. Here is how it differs from a proxy, SDK wrapper, and router, and when you need one.
The PromptUnit GitHub Action scans your PR diff for expensive models like GPT-4o and Claude Opus, and posts routing savings estimates automatically.
Tool use sends definitions on every turn and re-includes results in context. Agent loops compound the cost. Token bills run 3-5x projections. Here is the math and how to route around it.
OpenAI, Anthropic, Google, and Groq offer 50% off batch processing for async workloads. Stacked with caching, discounts reach 75-95%. Which tasks can actually wait?
Anthropic limited its strongest model to 50 partners at $25/$125 per million tokens. Here is why Project Glasswing pricing matters even if you cannot access it.
Gemini 2.5 Flash offers a 1M context window at $0.30/$2.50 per million tokens. Long-context vs. RAG routing depends on three questions most engineering teams never ask.
Gemma 4 31B hits 89.2% AIME at 855 t/s on one H100. The self-hosting break-even against API providers just dropped. Here is the routing math.
GPT-5.5 ships omnimodal architecture at $5/$30 per million tokens. Routing all multimodal calls to one model is tempting. Here is when to split instead.
A B2B analytics team cut AI spend from $12,400 to $6,960 per month. 43.9% reduction, zero impact on output quality. How PromptUnit identified the savings.
DeepSeek R2 beats o3 on MATH, GPQA, and AIME at $0.07/$0.27 per million tokens. Defaulting to o3 for reasoning costs a 30x premium. Here is how to route around it.
Groq LPUs run Llama 3.1 8B at $0.05/$0.08 per million tokens and 1,000 t/s. That is 10x the throughput of GPT-4o at 1/10th the cost. Which workloads should move?
DeepSeek V4 Pro hits frontier coding benchmarks at one-third the price of Claude Opus 4.7. Here is where it fits in your LLM routing stack.
GPT-5.5 launched at $5/$30 per million tokens, double GPT-5.4. Claude Opus 4.7 is at $5/$25 with the SWE-Bench lead. Here is what changed for cross-provider routing.
OpenAI's API, ChatGPT, and Codex went down on April 20, 2026 for hours. If your product broke, you have a single-provider problem. Here is the architecture fix.
GPT-5.4 mini scored 72.1% on OSWorld against the flagship's 75.0%, at 70% lower cost. Here is the routing math after the March 17 release.
How routing LLM traffic across OpenAI, Anthropic, and Google simultaneously reduces costs, improves reliability, and doesn't require compromising on quality.
A data-driven breakdown of real production LLM traffic showing which tasks actually require frontier models, and which are burning money unnecessarily.
A practical guide for engineering teams: which tasks GPT-4o-mini handles as well as GPT-4o, and where the quality trade-off is not worth the cost.
Beyond the API invoice: the real financial and operational cost of routing every LLM call to your most capable model, and the compounding effect over time.
A complete guide to LLM model routing: how it works, routing strategies, quality validation, and how to implement it without a codebase rewrite.
Current OpenAI API pricing for all major models, a practical cost calculator, and strategies to reduce your bill by 40–70% using intelligent model selection.
Most engineering teams are overpaying for LLM API calls by 50–70%. Here's exactly how to fix it, without touching your application code.
A technical explainer on AI inference proxies, what they do, how they differ from gateways and SDKs, and when they make sense for production LLM systems.